With advances in the field of natural language processing and voice recognition, the implementation of virtual assistants (also referred to herein as “virtual agents” or “VAs”) has flourished, allowing users to have access to personalized services that previously could only be provided by a real human. For example, some telephonic virtual agents provide static and/or dynamic information to the users via audio communications over a telephone call. Other virtual agents execute on user computing devices, such as smartphones and tablet computers, and provide access to a variety of services. For example, Siri® is a virtual agent available on some devices from Apple Computers, Inc., and the applications Google Now™ and several other virtual agents can be installed on user computing devices. Another type of virtual agent is utilized within the context of a real-time chat, such as a text or audio chat occurring at a merchant's website between a consumer and a representative of the merchant.
Some virtual agents are programmed to assist a user in performing various tasks. For example, a virtual agent may be programmed to send electronic messages, make appointments, place phone calls, and get directions. In completing such tasks, the virtual agent may interact with other applications (e.g., an email client) and may search for information either locally (e.g., from a user's electronic address book) or via one or more networks (e.g., from the World Wide Web, or Internet).
In the context of real-time chats, virtual agents are often configured to provide “self-service” content to consumers by providing answers to common questions. These virtual agent (VA) solutions are deployed to represent brands and to serve as an online customer service representative to guide the consumer to find information and answer their questions.
However, with many virtual agents, when an interaction is not successful (i.e., the VA is unable to understand or answer a user's question), the user may be redirected to other support channels. For example, some virtual agents in a real-time chat may respond to a customer question by stating, “Sorry, I couldn't answer your question, please call customer service at 1-800- . . . ” In other real-time chat implementations, when a virtual assistant is unable to assist a consumer, the consumer is redirected to another real-time chat with a “live” agent (i.e., a human), and must begin describing the situation to provide context for their questions all over again. In these scenarios, the consumer begins a real-time chat with a VA with the intention of solving their issue in real-time, but then needs to leave that conversational channel to continue the support interaction, mostly restarting the interaction from scratch, which ultimately creates a very poor customer experience.
Some approaches to eliminating the problems associated with imperfect virtual agents have been developed. For example, one approach involves building an integration between virtual agent technology and a live chat through “Guided Assistance” based on decision trees, which are used to present information to users in a human-like conversational form (or, as a knowledge search). When an escalation point is reached in the decision tree (i.e., a point in which the virtual agent may no longer provide assistance), a link (or URL) is presented to the user to allow the user to “escalate” to a live chat agent. This chat link, when selected by the user, opens a new chat module on the user's screen, and at most passes the last question asked by the consumer to the live chat agent. However, this approach keeps the virtual agent and the live agent separated from each other, and the live agent is, at most, only aware of a last question (or statement) entered by the consumer and is unaware of what has been discussed. Additionally, the live agent (or another human user, such as a supervisor) has no real visibility into what the virtual agent is doing with real consumers, or how well they are performing. Another approach includes utilizing virtual agents on the “backend” of a chat, such that the virtual agent does not directly interact with a consumer, but instead the virtual agent provides suggested responses to the live agent, which are only visible to the live chat agent. However, this approach does not fully utilize the original stated benefit of virtual agents, which is the reduction of the need for humans to be available to service routine consumer interactions.
Accordingly, there is a need for utilizing virtual agents within automated support channels with human-assisted customer support tools to provide flexible, economical, easily-managed, and effective chat-based assistance to consumers.